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Challenges in early detection and prognostication of sepsis: new approaches from the emergency department and intensive care unit

  • Thomas Lafon
  • , Melanie Weingart
  • , Julien Vaidie
  • , Carolyn S. Calfee
  • , Shevin T. Jacob
  • , Yonathan Freund
  • , Nathan I. Shapiro
  • , Olivier Barraud
  • , Guillaume Monneret
  • , Tom van der Poll
  • , Yeleen Fromage
  • , Bruno François
  • CHU de Limoges
  • University of California at San Francisco
  • Walimu
  • Sorbonne Université
  • Assistance publique – Hôpitaux de Paris
  • Beth Israel Deaconess Medical Center
  • Limoges University
  • Hospices civils de Lyon
  • Universite Claude Bernard Lyon 1
  • Academic Medical Center

Research output: Contribution to journalReview articlepeer-review

Abstract

In this narrative review, we aimed to provide a comprehensive overview of emerging diagnostic strategies and precision medicine approaches in sepsis, while explicitly acknowledging the heterogeneity of clinical contexts. In the Emergency Department (ED), timely recognition of infection and sepsis represents one of the most frequent and challenging tasks, which may delay management directly increasing morbidity and mortality. Even if very popular and widely used, traditional scores and routine biomarkers remain of limited interest to confirm diagnosis and predict deterioration. Nevertheless, emerging point-of-care tools hold promise such as “real-time microbiology”, bedside immune profiling, and echocardiography for on-time hemodynamic phenotyping. More advanced strategies, such as omics technologies and transcriptomic signatures, offer deeper biological precision, while machine learning and artificial intelligence can integrate high-dimensional ED data to anticipate deterioration and capture the dynamic evolution of sepsis subphenotypes. Many of these tools are already feasible at the bedside and only await integration into routine ED workflows. Embedding them within dedicated sepsis pathways and multidisciplinary teams could optimize global patient care and accelerate the transition toward precision medicine in acute sepsis. Sustainable improvements in sepsis outcomes will most likely not come from isolated devices but from their integration into coordinated and sepsis-specific pathways.

Original languageEnglish
Article number103864
JournaleClinicalMedicine
Volume94
DOIs
Publication statusPublished - 19 Apr 2026

Keywords

  • Artificial intelligence
  • Diagnosis
  • Emergency department
  • Phenotypes
  • Sepsis

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